Pandas Profiling Report

Dataset statistics

Number of variables	39
Number of observations	260601
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	77.5 MiB
Average record size in memory	312.0 B

Variable types

Numeric	9
Categorical	30

Alerts

`count_floors_pre_eq` is highly correlated with `height_percentage`	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage`	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage`	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`ground_floor_type` is highly correlated with `has_superstructure_cement_mortar_brick`	High correlation
`other_floor_type` is highly correlated with `roof_type`	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`roof_type` is highly correlated with `other_floor_type` and 1 other fields	High correlation
`has_superstructure_rc_engineered` is highly correlated with `foundation_type`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `foundation_type`	High correlation
`foundation_type` is highly correlated with `roof_type` and 4 other fields	High correlation
`has_superstructure_cement_mortar_brick` is highly correlated with `ground_floor_type` and 1 other fields	High correlation
`has_superstructure_rc_non_engineered` is highly correlated with `foundation_type`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`geo_level_1_id` is highly correlated with `foundation_type`	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage` and 1 other fields	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq` and 1 other fields	High correlation
`foundation_type` is highly correlated with `geo_level_1_id` and 2 other fields	High correlation
`roof_type` is highly correlated with `foundation_type` and 2 other fields	High correlation
`ground_floor_type` is highly correlated with `foundation_type` and 1 other fields	High correlation
`other_floor_type` is highly correlated with `count_floors_pre_eq` and 6 other fields	High correlation
`position` is highly correlated with `has_superstructure_mud_mortar_brick`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `other_floor_type` and 2 other fields	High correlation
`has_superstructure_mud_mortar_brick` is highly correlated with `position` and 1 other fields	High correlation
`has_superstructure_cement_mortar_brick` is highly correlated with `other_floor_type` and 1 other fields	High correlation
`has_superstructure_timber` is highly correlated with `has_superstructure_bamboo`	High correlation
`has_superstructure_bamboo` is highly correlated with `has_superstructure_timber`	High correlation
`has_superstructure_rc_non_engineered` is highly correlated with `other_floor_type`	High correlation
`has_superstructure_rc_engineered` is highly correlated with `other_floor_type`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`building_id` has unique values	Unique
`geo_level_1_id` has 4011 (1.5%) zeros	Zeros
`age` has 26041 (10.0%) zeros	Zeros
`count_families` has 20862 (8.0%) zeros	Zeros

Reproduction

Analysis started	2022-04-28 13:34:26.929837
Analysis finished	2022-04-28 13:36:23.133926
Duration	1 minute and 56.2 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

building_id
Real number (ℝ_≥0)

UNIQUE

Distinct	260601
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	525675.4828

Minimum	4
Maximum	1052934
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	4
5-th percentile	52114
Q1	261190
median	525757
Q3	789762
95-th percentile	1000724
Maximum	1052934
Range	1052930
Interquartile range (IQR)	528572

Descriptive statistics

Standard deviation	304544.999
Coefficient of variation (CV)	0.5793403136
Kurtosis	-1.203878964
Mean	525675.4828
Median Absolute Deviation (MAD)	264277
Skewness	0.001882356737
Sum	1.369915565 × 10¹¹
Variance	9.274765644 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
802906	1	< 0.1%
680296	1	< 0.1%
802531	1	< 0.1%
544902	1	< 0.1%
823257	1	< 0.1%
373540	1	< 0.1%
627590	1	< 0.1%
421951	1	< 0.1%
241191	1	< 0.1%
1024699	1	< 0.1%
Other values (260591)	260591	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	1	< 0.1%
8	1	< 0.1%
12	1	< 0.1%
16	1	< 0.1%
17	1	< 0.1%
25	1	< 0.1%
28	1	< 0.1%
31	1	< 0.1%
34	1	< 0.1%
36	1	< 0.1%

Value	Count	Frequency (%)
1052934	1	< 0.1%
1052931	1	< 0.1%
1052929	1	< 0.1%
1052926	1	< 0.1%
1052921	1	< 0.1%
1052915	1	< 0.1%
1052911	1	< 0.1%
1052909	1	< 0.1%
1052908	1	< 0.1%
1052906	1	< 0.1%

geo_level_1_id
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	31
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.90035341

Minimum	0
Maximum	30
Zeros	4011
Zeros (%)	1.5%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	7
median	12
Q3	21
95-th percentile	27
Maximum	30
Range	30
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	8.033616625
Coefficient of variation (CV)	0.5779433361
Kurtosis	-1.213248785
Mean	13.90035341
Median Absolute Deviation (MAD)	6
Skewness	0.2725303548
Sum	3622446
Variance	64.53899608
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
6	24381	9.4%
26	22615	8.7%
10	22079	8.5%
17	21813	8.4%
8	19080	7.3%
7	18994	7.3%
20	17216	6.6%
21	14889	5.7%
4	14568	5.6%
27	12532	4.8%
Other values (21)	72434	27.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4011	1.5%
1	2701	1.0%
2	931	0.4%
3	7540	2.9%
4	14568	5.6%
5	2690	1.0%
6	24381	9.4%
7	18994	7.3%
8	19080	7.3%
9	3958	1.5%

Value	Count	Frequency (%)
30	2686	1.0%
29	396	0.2%
28	265	0.1%
27	12532	4.8%
26	22615	8.7%
25	5624	2.2%
24	1310	0.5%
23	1121	0.4%
22	6252	2.4%
21	14889	5.7%

geo_level_2_id
Real number (ℝ_≥0)

Distinct	1414
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	701.0746851

Minimum	0
Maximum	1427
Zeros	38
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	0
5-th percentile	69
Q1	350
median	702
Q3	1050
95-th percentile	1377
Maximum	1427
Range	1427
Interquartile range (IQR)	700

Descriptive statistics

Standard deviation	412.7107336
Coefficient of variation (CV)	0.5886829782
Kurtosis	-1.188232475
Mean	701.0746851
Median Absolute Deviation (MAD)	349
Skewness	0.02895738139
Sum	182700764
Variance	170330.1496
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
39	4038	1.5%
158	2520	1.0%
181	2080	0.8%
1387	2040	0.8%
157	1897	0.7%
363	1760	0.7%
463	1740	0.7%
673	1704	0.7%
533	1684	0.6%
883	1626	0.6%
Other values (1404)	239512	91.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	38	< 0.1%
1	204	0.1%
3	77	< 0.1%
4	315	0.1%
5	25	< 0.1%
6	2	< 0.1%
7	100	< 0.1%
8	120	< 0.1%
9	333	0.1%
10	354	0.1%

Value	Count	Frequency (%)
1427	6	< 0.1%
1426	286	0.1%
1425	466	0.2%
1424	7	< 0.1%
1423	3	< 0.1%
1422	216	0.1%
1421	254	0.1%
1420	10	< 0.1%
1419	95	< 0.1%
1418	152	0.1%

geo_level_3_id
Real number (ℝ_≥0)

Distinct	11595
Distinct (%)	4.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6257.876148

Minimum	0
Maximum	12567
Zeros	2
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	0
5-th percentile	611
Q1	3073
median	6270
Q3	9412
95-th percentile	11927
Maximum	12567
Range	12567
Interquartile range (IQR)	6339

Descriptive statistics

Standard deviation	3646.369645
Coefficient of variation (CV)	0.5826848532
Kurtosis	-1.213896506
Mean	6257.876148
Median Absolute Deviation (MAD)	3171
Skewness	0.0003935120899
Sum	1630808782
Variance	13296011.59
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
633	651	0.2%
9133	647	0.2%
621	530	0.2%
11246	470	0.2%
2005	466	0.2%
11440	455	0.2%
7723	443	0.2%
9229	381	0.1%
2452	349	0.1%
12258	312	0.1%
Other values (11585)	255897	98.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	< 0.1%
1	6	< 0.1%
3	9	< 0.1%
5	14	< 0.1%
6	21	< 0.1%
7	2	< 0.1%
8	31	< 0.1%
9	3	< 0.1%
10	1	< 0.1%
11	62	< 0.1%

Value	Count	Frequency (%)
12567	1	< 0.1%
12565	7	< 0.1%
12564	6	< 0.1%
12563	24	< 0.1%
12562	3	< 0.1%
12561	19	< 0.1%
12560	17	< 0.1%
12559	6	< 0.1%
12558	6	< 0.1%
12557	44	< 0.1%

count_floors_pre_eq
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.129723217

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	2
95-th percentile	3
Maximum	9
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7276645453
Coefficient of variation (CV)	0.3416709456
Kurtosis	2.322597881
Mean	2.129723217
Median Absolute Deviation (MAD)	0
Skewness	0.8341129586
Sum	555008
Variance	0.5294956905
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	156623	60.1%
3	55617	21.3%
1	40441	15.5%
4	5424	2.1%
5	2246	0.9%
6	209	0.1%
7	39	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	40441	15.5%
2	156623	60.1%
3	55617	21.3%
4	5424	2.1%
5	2246	0.9%
6	209	0.1%
7	39	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
8	1	< 0.1%
7	39	< 0.1%
6	209	0.1%
5	2246	0.9%
4	5424	2.1%
3	55617	21.3%
2	156623	60.1%
1	40441	15.5%

age
Real number (ℝ_≥0)

ZEROS

Distinct	42
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.53502865

Minimum	0
Maximum	995
Zeros	26041
Zeros (%)	10.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	10
median	15
Q3	30
95-th percentile	60
Maximum	995
Range	995
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	73.56593652
Coefficient of variation (CV)	2.772408408
Kurtosis	157.2482363
Mean	26.53502865
Median Absolute Deviation (MAD)	10
Skewness	12.19249422
Sum	6915055
Variance	5411.947016
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=42)

Value	Count	Frequency (%)
10	38896	14.9%
15	36010	13.8%
5	33697	12.9%
20	32182	12.3%
0	26041	10.0%
25	24366	9.3%
30	18028	6.9%
35	10710	4.1%
40	10559	4.1%
50	7257	2.8%
Other values (32)	22855	8.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	26041	10.0%
5	33697	12.9%
10	38896	14.9%
15	36010	13.8%
20	32182	12.3%
25	24366	9.3%
30	18028	6.9%
35	10710	4.1%
40	10559	4.1%
45	4711	1.8%

Value	Count	Frequency (%)
995	1390	0.5%
200	106	< 0.1%
195	2	< 0.1%
190	3	< 0.1%
185	1	< 0.1%
180	7	< 0.1%
175	5	< 0.1%
170	6	< 0.1%
165	2	< 0.1%
160	6	< 0.1%

area_percentage
Real number (ℝ_≥0)

Distinct	84
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.018050583

Minimum	1
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	5
median	7
Q3	9
95-th percentile	16
Maximum	100
Range	99
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	4.392230936
Coefficient of variation (CV)	0.5477928694
Kurtosis	30.43825794
Mean	8.018050583
Median Absolute Deviation (MAD)	2
Skewness	3.526082314
Sum	2089512
Variance	19.29169259
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	42013	16.1%
7	36752	14.1%
5	32724	12.6%
8	28445	10.9%
9	22199	8.5%
4	19236	7.4%
10	15613	6.0%
11	13907	5.3%
3	11837	4.5%
12	7581	2.9%
Other values (74)	30294	11.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	90	< 0.1%
2	3181	1.2%
3	11837	4.5%
4	19236	7.4%
5	32724	12.6%
6	42013	16.1%
7	36752	14.1%
8	28445	10.9%
9	22199	8.5%
10	15613	6.0%

Value	Count	Frequency (%)
100	1	< 0.1%
96	3	< 0.1%
90	1	< 0.1%
86	5	< 0.1%
85	4	< 0.1%
84	3	< 0.1%
83	3	< 0.1%
82	1	< 0.1%
80	1	< 0.1%
78	1	< 0.1%

height_percentage
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	27
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.434365179

Minimum	2
Maximum	32
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	4
median	5
Q3	6
95-th percentile	9
Maximum	32
Range	30
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.918418221
Coefficient of variation (CV)	0.3530160667
Kurtosis	14.31852616
Mean	5.434365179
Median Absolute Deviation (MAD)	1
Skewness	1.808261757
Sum	1416201
Variance	3.68032847
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
5	78513	30.1%
6	46477	17.8%
4	37763	14.5%
7	35465	13.6%
3	25957	10.0%
8	13902	5.3%
2	9305	3.6%
9	5376	2.1%
10	4492	1.7%
11	917	0.4%
Other values (17)	2434	0.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	9305	3.6%
3	25957	10.0%
4	37763	14.5%
5	78513	30.1%
6	46477	17.8%
7	35465	13.6%
8	13902	5.3%
9	5376	2.1%
10	4492	1.7%
11	917	0.4%

Value	Count	Frequency (%)
32	75	< 0.1%
31	1	< 0.1%
28	2	< 0.1%
26	2	< 0.1%
25	3	< 0.1%
24	4	< 0.1%
23	11	< 0.1%
21	13	< 0.1%
20	33	< 0.1%
19	7	< 0.1%

land_surface_condition
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

t	216757
n	35528
o	8316

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	t
2nd row	o
3rd row	t
4th row	t
5th row	t

Common Values

Value	Count	Frequency (%)
t	216757	83.2%
n	35528	13.6%
o	8316	3.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
t	216757	83.2%
n	35528	13.6%
o	8316	3.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

foundation_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

r	219196
w	15118
u	14260
i	10579
h	1448

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	r
2nd row	r
3rd row	r
4th row	r
5th row	r

Common Values

Value	Count	Frequency (%)
r	219196	84.1%
w	15118	5.8%
u	14260	5.5%
i	10579	4.1%
h	1448	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
r	219196	84.1%
w	15118	5.8%
u	14260	5.5%
i	10579	4.1%
h	1448	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

roof_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

n	182842
q	61576
x	16183

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	n
2nd row	n
3rd row	n
4th row	n
5th row	n

Common Values

Value	Count	Frequency (%)
n	182842	70.2%
q	61576	23.6%
x	16183	6.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
n	182842	70.2%
q	61576	23.6%
x	16183	6.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ground_floor_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

f	209619
x	24877
v	24593
z	1004
m	508

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	f
2nd row	x
3rd row	f
4th row	f
5th row	f

Common Values

Value	Count	Frequency (%)
f	209619	80.4%
x	24877	9.5%
v	24593	9.4%
z	1004	0.4%
m	508	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	209619	80.4%
x	24877	9.5%
v	24593	9.4%
z	1004	0.4%
m	508	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

other_floor_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

q	165282
x	43448
j	39843
s	12028

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	q
2nd row	q
3rd row	x
4th row	x
5th row	x

Common Values

Value	Count	Frequency (%)
q	165282	63.4%
x	43448	16.7%
j	39843	15.3%
s	12028	4.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
q	165282	63.4%
x	43448	16.7%
j	39843	15.3%
s	12028	4.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

position
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

s	202090
t	42896
j	13282
o	2333

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	t
2nd row	s
3rd row	t
4th row	s
5th row	s

Common Values

Value	Count	Frequency (%)
s	202090	77.5%
t	42896	16.5%
j	13282	5.1%
o	2333	0.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
s	202090	77.5%
t	42896	16.5%
j	13282	5.1%
o	2333	0.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

plan_configuration
Categorical

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

d	250072
q	5692
u	3649
s	346
c	325
Other values (5)	517

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	d
2nd row	d
3rd row	d
4th row	d
5th row	d

Common Values

Value	Count	Frequency (%)
d	250072	96.0%
q	5692	2.2%
u	3649	1.4%
s	346	0.1%
c	325	0.1%
a	252	0.1%
o	159	0.1%
m	46	< 0.1%
n	38	< 0.1%
f	22	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
d	250072	96.0%
q	5692	2.2%
u	3649	1.4%
s	346	0.1%
c	325	0.1%
a	252	0.1%
o	159	0.1%
m	46	< 0.1%
n	38	< 0.1%
f	22	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_adobe_mud
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	237500
1	23101

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	237500	91.1%
1	23101	8.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	237500	91.1%
1	23101	8.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_mud_mortar_stone
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

1	198561
0	62040

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	198561	76.2%
0	62040	23.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	198561	76.2%
0	62040	23.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_stone_flag
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	251654
1	8947

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	251654	96.6%
1	8947	3.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	251654	96.6%
1	8947	3.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_cement_mortar_stone
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	255849
1	4752

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	255849	98.2%
1	4752	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	255849	98.2%
1	4752	1.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_mud_mortar_brick
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	242840
1	17761

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	242840	93.2%
1	17761	6.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	242840	93.2%
1	17761	6.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_cement_mortar_brick
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	240986
1	19615

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	240986	92.5%
1	19615	7.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	240986	92.5%
1	19615	7.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_timber
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	194151
1	66450

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	194151	74.5%
1	66450	25.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	194151	74.5%
1	66450	25.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_bamboo
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	238447
1	22154

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	238447	91.5%
1	22154	8.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	238447	91.5%
1	22154	8.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_rc_non_engineered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	249502
1	11099

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	249502	95.7%
1	11099	4.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	249502	95.7%
1	11099	4.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_rc_engineered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	256468
1	4133

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	256468	98.4%
1	4133	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	256468	98.4%
1	4133	1.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_other
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	256696
1	3905

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	256696	98.5%
1	3905	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	256696	98.5%
1	3905	1.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

legal_ownership_status
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

v	250939
a	5512
w	2677
r	1473

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	v
2nd row	v
3rd row	v
4th row	v
5th row	v

Common Values

Value	Count	Frequency (%)
v	250939	96.3%
a	5512	2.1%
w	2677	1.0%
r	1473	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
v	250939	96.3%
a	5512	2.1%
w	2677	1.0%
r	1473	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

count_families
Real number (ℝ_≥0)

ZEROS

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9839486418

Minimum	0
Maximum	9
Zeros	20862
Zeros (%)	8.0%
Negative	0
Negative (%)	0.0%
Memory size	2.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	2
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4183889779
Coefficient of variation (CV)	0.425214244
Kurtosis	17.67094319
Mean	0.9839486418
Median Absolute Deviation (MAD)	0
Skewness	1.634757873
Sum	256418
Variance	0.1750493368
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	226115	86.8%
0	20862	8.0%
2	11294	4.3%
3	1802	0.7%
4	389	0.1%
5	104	< 0.1%
6	22	< 0.1%
7	7	< 0.1%
9	4	< 0.1%
8	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20862	8.0%
1	226115	86.8%
2	11294	4.3%
3	1802	0.7%
4	389	0.1%
5	104	< 0.1%
6	22	< 0.1%
7	7	< 0.1%
8	2	< 0.1%
9	4	< 0.1%

Value	Count	Frequency (%)
9	4	< 0.1%
8	2	< 0.1%
7	7	< 0.1%
6	22	< 0.1%
5	104	< 0.1%
4	389	0.1%
3	1802	0.7%
2	11294	4.3%
1	226115	86.8%
0	20862	8.0%

has_secondary_use
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	231445
1	29156

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	231445	88.8%
1	29156	11.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	231445	88.8%
1	29156	11.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_agriculture
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	243824
1	16777

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	243824	93.6%
1	16777	6.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	243824	93.6%
1	16777	6.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_hotel
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	251838
1	8763

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	251838	96.6%
1	8763	3.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	251838	96.6%
1	8763	3.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_rental
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	258490
1	2111

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	258490	99.2%
1	2111	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	258490	99.2%
1	2111	0.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_institution
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260356
1	245

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260356	99.9%
1	245	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260356	99.9%
1	245	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_school
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260507
1	94

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260507	> 99.9%
1	94	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260507	> 99.9%
1	94	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_industry
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260322
1	279

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260322	99.9%
1	279	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260322	99.9%
1	279	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_health_post
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260552
1	49

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260552	> 99.9%
1	49	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260552	> 99.9%
1	49	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_gov_office
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260563
1	38

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260563	> 99.9%
1	38	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260563	> 99.9%
1	38	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_use_police
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	260578
1	23

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	260578	> 99.9%
1	23	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	260578	> 99.9%
1	23	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_other
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

0	259267
1	1334

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	259267	99.5%
1	1334	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	259267	99.5%
1	1334	0.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	building_id	geo_level_1_id	geo_level_2_id	geo_level_3_id	count_floors_pre_eq	age	area_percentage	height_percentage	land_surface_condition	foundation_type	roof_type	ground_floor_type	other_floor_type	position	plan_configuration	has_superstructure_adobe_mud	has_superstructure_mud_mortar_stone	has_superstructure_cement_mortar_brick	has_superstructure_timber	has_superstructure_bamboo	legal_ownership_status	count_families	has_secondary_use	has_secondary_use_agriculture
0	802906	6	487	12198	2	30	6	5	t	r	n	f	q	t	d	1	1	0	0	0	v	1	0	0
1	28830	8	900	2812	2	10	8	7	o	r	n	x	q	s	d	0	1	0	0	0	v	1	0	0
2	94947	21	363	8973	2	10	5	5	t	r	n	f	x	t	d	0	1	0	0	0	v	1	0	0
3	590882	22	418	10694	2	10	6	5	t	r	n	f	x	s	d	0	1	0	1	1	v	1	0	0
4	201944	11	131	1488	3	30	8	9	t	r	n	f	x	s	d	1	0	0	0	0	v	1	0	0
5	333020	8	558	6089	2	10	9	5	t	r	n	f	q	s	d	0	1	0	0	0	v	1	1	1
6	728451	9	475	12066	2	25	3	4	n	r	n	x	q	s	d	0	1	0	0	0	v	1	0	0
7	475515	20	323	12236	2	0	8	6	t	w	q	v	x	s	u	0	0	1	1	0	v	1	0	0
8	441126	0	757	7219	2	15	8	6	t	r	q	f	q	s	d	0	1	0	1	0	v	1	0	0
9	989500	26	886	994	1	0	13	4	t	i	n	v	j	s	d	0	0	1	0	0	v	1	0	0

Last rows

	building_id	geo_level_1_id	geo_level_2_id	geo_level_3_id	count_floors_pre_eq	age	area_percentage	height_percentage	land_surface_condition	foundation_type	roof_type	ground_floor_type	other_floor_type	position	plan_configuration	has_superstructure_mud_mortar_stone	has_superstructure_mud_mortar_brick	has_superstructure_cement_mortar_brick	has_superstructure_timber	legal_ownership_status	count_families	has_secondary_use	has_secondary_use_agriculture
260591	560805	20	368	5980	1	25	5	3	n	r	n	f	j	s	d	1	0	0	0	v	1	1	1
260592	207683	10	1382	1903	2	25	5	5	t	r	n	f	q	s	d	1	0	0	1	v	1	0	0
260593	226421	8	767	8613	2	5	13	5	t	r	n	f	q	s	d	1	0	0	0	v	1	1	1
260594	159555	27	181	1537	6	0	13	12	t	r	n	f	x	j	d	0	1	0	0	v	1	0	0
260595	827012	8	268	4718	2	20	8	5	t	r	n	f	q	s	d	1	0	0	0	v	1	0	0
260596	688636	25	1335	1621	1	55	6	3	n	r	n	f	j	s	q	1	0	0	0	v	1	0	0
260597	669485	17	715	2060	2	0	6	5	t	r	n	f	q	s	d	1	0	0	0	v	1	0	0
260598	602512	17	51	8163	3	55	6	7	t	r	q	f	q	s	d	1	0	0	0	v	1	0	0
260599	151409	26	39	1851	2	10	14	6	t	r	x	v	s	j	d	0	0	1	0	v	1	0	0
260600	747594	21	9	9101	3	10	7	6	n	r	n	f	q	j	d	1	0	0	0	v	3	0	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script